Guinea vs Sierra Leone: Trading across borders: Documents to import (number) (DB06-15 methodol

Guinea
53.85
in 2014
Sierra Leone
53.85
in 2014
Guinea rank
105th
Sierra Leone rank
105th

Trading across borders: Documents to import (number) (DB06-15 methodol over time

  • Guinea
  • Sierra Leone
0204060200520092014

How they compare

Guinea currently reports 53.85 against 53.85 in Sierra Leone, a difference of 0.

Across all 10 years both countries report, Sierra Leone has been ahead every year.

Guinea ranks 105th and Sierra Leone ranks 105th of 181 countries.

Head to head by decade

Decade Guinea Sierra Leone Difference Ahead
2000s 53.85 53.85 0
2010s 53.85 53.85 0

Averages of every year both report within each decade.

Frequently asked questions

Which has higher trading across borders: documents to import (number) (db06-15 methodol, Guinea or Sierra Leone?
Guinea, at 53.85 against 53.85 in Sierra Leone as of 2014.
What is the difference in trading across borders: documents to import (number) (db06-15 methodol between Guinea and Sierra Leone?
0, with Guinea ahead.
How many years of comparable data are there for Guinea and Sierra Leone?
10 years are reported by both, from 2005 to 2014.
How do Guinea and Sierra Leone rank globally for trading across borders: documents to import (number) (db06-15 methodol?
Guinea ranks 105th and Sierra Leone ranks 105th of 181 countries.
Where does this data come from?
The World Bank, published as Trading across borders: Documents to import (number) (DB06-15 methodology) - Score. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

About this data

Indicator
Trading across borders: Documents to import (number) (DB06-15 methodology) - Score
Source
World Bank
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
183 places, 1,813 data points, 2005–2014
Last refreshed

The score for the number of documents to import benchmarks economies with respect to the regulatory best practice on the indicator. The score ranges from 0 to 100, where 0 represents the worst regulatory performance and 100 the best regulatory performance, and is computed based on the methodology in the DB06-15 studies.